JP2019135507A - Learning support device and program - Google Patents

Abstract

To notify a coach of information effective to student guidance or learning follow-up at an appropriate timing in an easily recognizable manner.SOLUTION: The learning support device comprises: means for extracting questions belonging to one or more units for each learning session determining a type of an action that a coach who instructs students should take, and for providing the extracted questions to the students, and for inputting answer data and learning state data; learning level calculation means for calculating learning levels of the students with respect to the unit whose lecture the students take on the basis of the input answer data, and for determining whether or not the learning levels have reached a threshold; learning level prediction means for predicating and calculating future learning levels of the students; action timing determination means for classifying the respective students into any of a plurality of categories by using at least one of the learning state data of each student, an arithmetic result of the learning level calculation means and an arithmetic result of the learning level prediction means; and means for making identifiable which of the categories the students belong to, and for generating learning state list data of the students.SELECTED DRAWING: Figure 1

Description

  The present invention relates to a learning support device that provides a student's learning progress to an instructor (hereinafter referred to as a “coach”), and in particular, effectively relates the progress of a plurality of students with different progress to a coach terminal device. The present invention relates to a learning support apparatus and a program that can be displayed.

  2. Description of the Related Art Conventionally, in learning instruction for students, a technique has been proposed in which information necessary for a coach to perform learning instruction, such as learning progress and proficiency (understanding level), is transmitted to the terminal device of the coach.

  For example, in Patent Document 1, in order to advance the course appropriately even if there is a difference in the progress among the students, the method of progress is determined by the level of understanding of the students in the course using content in each chapter of the course curriculum It is described that the degree of understanding of each student is aggregated and the course is automatically advanced according to the follow condition or at the discretion of a part of the instructor.

  Patent Document 2 proposes a lesson management system in which the learning progress of each student at each checkpoint is sent to the instructor terminal in a lump and the checkpoint can be changed by an instruction from the instructor terminal. Yes.

JP 2014-85467 A Japanese Patent No. 35679797

  However, the above-described conventional technology only transmits data at that time such as the proficiency level and progress of students to the coach terminal in real time. So, for example, when a student achieves a goal and calls out, “You did your best,” the coach will constantly monitor the data sent in real time to achieve the goal. It is necessary to promptly recognize and speak to the students who have completed. If the number of students is small, it is possible to constantly monitor the progress of each student, but if the number of students is large, the burden on the coach becomes excessive.

  The present invention has been made in response to such a conventional situation, and provides a learning support apparatus and program capable of easily and easily informing the coach of action timing effective for student guidance and learning follow-up such as calling out to students. The purpose is to provide.

In order to achieve the above object, the learning support device of the present invention provides:
This is a learning support device that stores questions to be asked for each unit, provides students with questions that belong to the unit that the student takes, and inputs the answer data to calculate the timing of the action to be taken by the coach who teaches the student. And
For each learning session that defines the type of action, questions that belong to one or more units are extracted, the extracted questions are provided to the student, answer data is input, and whether the student has finished the learning session Means for inputting learning status data including
A proficiency level calculating means for calculating the proficiency level of the student for the unit to which the problem provided to the student belongs based on the input answer data, and determining whether the proficiency level has reached a threshold;
A proficiency level prediction means for calculating the future proficiency level of the student for the unit that the student takes,
Classifying each student into one of a plurality of categories using at least one of the learning status data of each student, the calculation result of the proficiency level calculation means, and the calculation result of the proficiency level prediction means Action timing determination means for
An editing means for generating a list of learning statuses of the student by making it possible to identify which of the categories the student belongs to;
An output means for outputting the learning status list data;
It is provided with.

  Here, the proficiency level means the degree to which the student understands a certain learning field (unit), but also includes the so-called estimated proficiency level in consideration of interval estimation and probability distribution.

  In addition, the type of action is, for example, a so-called “encouragement system” that encourages students to “do their best” when they pass a certain unit, and students solve the same problem for a long time or watch lectures. There is a so-called “help system” type that gives advice when neglecting or not reading an answer to a wrong problem. Different types of actions are performed by the instructor depending on whether or not it is during a learning session. Specifically, help-type actions are executed during the learning session, and encouragement-type actions are executed when not in the learning session.

  In the present invention, not only the current proficiency level of the student but also the future proficiency level is predicted, and the student's learning status list is created based on the prediction result. It becomes possible to grasp in advance with high accuracy.

  The proficiency level prediction means is based on a certain level of an existing learning session, for example, an answer history of a student who has passed a passing level in a learning session, an answer history of a calculation target student, and a number of consecutive correct answers of the calculation target student. Alternatively, the student's proficiency level can be predicted and calculated by virtually setting the correctness / incorrectness of a question that is currently being answered or scheduled to be answered by the student to be calculated.

  In addition, the coach can easily make the action target student and the action target soon by displaying the student of a specific category at the top of the screen, adding an identification symbol, or identifying and displaying by a color change display or the like by the editing means. Can recognize the students who will become, and can reduce the burden on the coach.

  As described above, according to the present invention, it is possible to easily recognize to the coach the timing of actions effective for student guidance and learning follow-up such as speaking to students. This allows the coach to take action at an appropriate time for each of the students.

It is a functional block diagram of the learning assistance system by the 1st Embodiment of this invention. It is an example of a data structure of attendance history DB of FIG. It is a data structural example of the learning condition table of FIG. Processing procedure of proficiency level prediction means in FIG. It is a table block diagram used in the other Example of the proficiency level prediction means of FIG. It is a flowchart which shows the process sequence of the action timing determination means of FIG. It is a figure which shows the screen of the learning condition list displayed on the coach terminal 2 of FIG. It is a flowchart which shows the process sequence of the action timing determination means by the 2nd Embodiment of this invention. It is the table which linked | related the student and seat position by the 2nd Embodiment of this invention. It is a figure which shows the screen of a student seat position and learning status list displayed on the coach terminal of FIG.

[First Embodiment]
A learning support system according to a first embodiment of the present invention will be described below with reference to the drawings. FIG. 1 is a functional block diagram of a learning support system 1 according to this embodiment.

  In the learning support system 1, the learning support device 10 is connected to the coach terminal 2 and the student terminal 3 via the communication network 4. Here, the learning support system 1 is configured by a client server model, a cloud computing form, or the like, but is not limited thereto.

  The learning support apparatus 10 includes a transmission / reception unit 11 for communicating with the coach terminal 2 and the student terminal 3 via the communication network 4, a storage unit 12 for storing data, and an arithmetic processing unit 13 for executing data processing. Yes.

  The arithmetic processing unit 13 transmits student content such as viewing data and problems displayed on the student terminal, and receives student data such as answers and learning status sent from the student terminal 3 (hereinafter referred to as student terminal interface means). , “Student terminal I / F means”) 31, timer means 2 (39) provided for each student and restarting time measurement at the start of each unit in the learning session according to instructions from the student terminal I / F means 31 , Timer means 1 (38) for restarting time measurement at the end of each learning session, proficiency level calculating means 32 for determining the proficiency level of the unit that the student is attending, and students attending based on the proficiency level New pass determination means 33 for determining whether or not the unit to be passed for the first time, predicting the proficiency level based on the correctness / incorrectness of the problem that the student is currently answering or will answer in the future, or has proficiency level Based on the proficiency level prediction means 34 for calculating the number of questions to be answered correctly or the time until the proficiency level becomes equal to or higher than the threshold value, for example, the student's learning status and proficiency level, etc. Action timing determination means 35 for determining the timing of actions to be taken by the coach, such as calling to the student, and editing for generating a list of student learning statuses to be notified to the coach terminal 2 based on the determination result of the action timing determination means 35 Means 36 and coach terminal interface means (hereinafter referred to as “coach terminal I / F means”) 37 for transmitting the learning status list data to the coach terminal 2 are provided.

  In addition, each means 31-39 of the arithmetic processing part 13 is realizable with a program as a function of CPU.

  The student DB 21 stores student attribute information such as the name and ID of the student and information such as the unit to be attended, and the educational content DB 22 provides educational content such as diagnostic test questions, lecture content, and review test questions for each unit. Is saved.

  The attendance history DB 23 stores history data such as a unit attended by a student, test results (answer correctness), and proficiency level of each unit. The learning status table 24 stores the learning status of the student and is updated in real time.

Next, the operation of the learning support system 1 having the above configuration will be described.
The learning support apparatus 10 transmits content data stored in the educational content DB 22 for each activity (diagnosis, lecture, review) included in the learning session via the student terminal I / F unit 31. To each student terminal 3. Here, the diagnosis confirms in advance how much the student has knowledge about the learning session, and is determined by, for example, an answer to a problem prepared in advance. Lectures are delivered by distributing video / still image data. In addition, the review is to determine the level of proficiency by distributing problems prepared in advance for a unit that has been taken or taken after a lecture or after a predetermined period of time, and scoring the answers. Lecture data and questions may be distributed in a predetermined order, or problem data may be distributed after lecture data, and the next lecture data to be distributed may be determined based on whether the answer is correct or incorrect. .

  When the student terminal 3 receives the content data sent from the learning support device 10, it outputs it on the screen. Based on this content data, each student can view the lecture content, or assist the student through the student terminal 3 to answer the diagnostic test that is performed when the learning session is selected and the review test that is performed after viewing the lecture content. Transmit to device 10.

  When the student terminal I / F unit 31 of the learning support device 10 receives the data sent from the student terminal 3 via the transmission / reception unit 11, the student terminal I / F unit 31 stores the data in the attendance history DB 23 and learns the student in the learning status table 24. Update status data.

  FIG. 2 is a data configuration example of the attendance history DB 23. For each student ID, the session ID, the problem ID, the start time and end time of the problem, and the proficiency level of the unit that the student attends at the time when the problem is completed are stored. In FIG. 2, the symbol at the head of the problem ID is for identifying the unit. Therefore, the unit that the student has taken can be identified from the problem ID.

  FIG. 3 is a data configuration example of the learning status table 24. For each student identification information (student ID), learning session identification information, a learning session flag indicating whether or not learning is in progress, a new pass flag indicating whether or not the unit in the learning session has been passed for the first time, proficiency level prediction The shortest number of problems (predicted value) until the unit pass calculated by the means 33 and data of each item of the display form to be described later are stored. Note that the learning status table 24 does not have to be a single type of table as shown in FIG. 3. For example, it is sufficient if each item can be searched using the student ID as a key. It is assumed that each column of the learning status table 24 is set to an arbitrary value that can be used to determine whether or not the calculation is not performed when the learning support device 10 is initialized.

  The student terminal I / F unit 31 of the learning support device 10 extracts a unit problem to be distributed in units of learning sessions, which are a series of learning units, and distributes the extracted problems to the student terminal 3 for each student. This learning session defines the type of action to be taken by the coach. When the student terminal I / F unit 31 receives the answer data from the student after distributing the question, the student terminal I / F unit 31 determines whether the answer is correct, stores the result in the attendance history DB 23 and activates the proficiency level calculating unit 32.

(Proficiency level calculation processing)
When activated, the proficiency level calculation means 32 calculates the proficiency level of the unit based on the answer data. Note that the ID of the answer data is associated with the question ID, thereby enabling the unit to be specified.

  As a method of calculating the proficiency level, for example, existing techniques such as JP 2012-93599 A, JP 2007-248773 A, and JP 2006-23566 A can be used. As a simple method, the proficiency level can be the correct answer rate (correct answer number / predetermined number) of answers to the most recent predetermined number of questions (for example, five questions). Alternatively, the level of proficiency may be calculated by performing weighting according to the order of questions from the start of the session, or performing weighting in consideration of the correct answer rate of the students who have questioned each question.

  Then, the proficiency level calculation means 32 sets a pass flag when the calculated proficiency level is equal to or greater than a predetermined value (pass threshold). At this time, when the student has passed the unit for the first time, the new pass determination means 33 sets a new pass flag in the unit column of the learning status table 24. This flag is reset via the coach terminal 2 when the coach takes action on the student. In addition, the number of times of passing is stored in the new pass flag column shown in FIG. That is, “0” when not passed, “1” when newly passed, “2” when the number of times passed is 2, and so on. In this case, it is determined that the new pass flag is set when the value of the new pass flag column is “1”. In addition, when passing, “0” is written in a predicted value column (hereinafter also simply referred to as “predicted value column”) until the student passes the student in the learning status table 24.

(Proficiency level prediction process)
Next, the processing procedure of the proficiency level prediction unit 34 will be described with reference to FIG.
The proficiency level predicting means 34 first extracts correct / incorrect data from the attendance history DB 23 when the student terminal I / F means 31 is activated at the time of problem assignment to the student terminal (S101). The number of correct answers up to the present in the unit is stored in the variable X, and the number of incorrect answers is stored in the variable Y (S102). Further, the number of remaining questions of the unit is extracted from the educational content DB 22 (S103), and stored in the variable Z (S104). Incidentally, the number of remaining questions can be updated at the time of distribution of the problem to the student terminal, but in the present embodiment, it is assumed that it has been updated before the proficiency level predicting means 34 is activated. Therefore, when the last problem of the unit is distributed, the remaining problem number becomes “0”.

  The proficiency level predicting means 34 next sets the variable T to the initial value “1” (S105). This variable T represents the number that must be continuously answered in the future including the currently distributed problem before the prediction calculation target student passes the unit.

  Then, the sum of the value of the variable X and the value of the variable T is stored in the variable X (S106), and the proficiency level calculation means 32 is activated (S107). When the proficiency level calculation means 32 is activated, the proficiency level is calculated using the value of the variable X and other data required for the proficiency level calculation (for example, the number of incorrect answers Y).

  In step S108, the proficiency level predicting unit 34 determines whether or not the calculation result of the proficiency level calculating unit 32 is equal to or greater than a pass threshold value. A value is written (S109).

  If the proficiency level calculated in step S108 is smaller than the acceptance threshold value in step S108, the proficiency level predicting unit 34 next determines whether the variable Z is “0” (S110). In the case of “0”, a predetermined code (for example, 99) indicating that the possibility of passing the unit is zero is written in the predicted value column of the learning status table 24 (S111).

  On the other hand, if “NO” in the step S110, the variable Z is decremented, the variable T is incremented (S112, S113), the process returns to the step S106, and the subsequent processing is repeated.

As a result of the above processing, the predicted value column of the learning status table 24 means that if the value is “1”, it will pass if the currently distributed problem is correctly answered. That is, the value column n (n is an integer) represents the number of questions that the student should correctly answer, including the problem that is currently being distributed.
In the above prediction calculation, the problem may be one question at a time, or a set of a plurality of problems. In other words, it is preferably performed for each group of problems that the student performs continuously.
As described above, the proficiency level prediction calculation is performed not when the answer to the question is received but when the question is distributed, so that the coach can be notified in advance of an alert for action at an appropriate timing.

  In addition, the above explanation is based on the assumption that the problem or problem group performed by the student is delivered to the student terminal each time. For example, for each unit or session, the problem group belonging to the unit or session is collectively sent to the student terminal. You may make it deliver. In this case, when the student terminal recognizes that the student has started the problem or problem group, the learning support apparatus 10 is notified that the student has started. This recognition method may be, for example, when the problem is displayed on the display screen of the student terminal 3 or when the student terminal 3 detects that the student has selected the problem. When the student terminal I / F means 31 detects from the student terminal 3 that the student has started the problem, the student terminal I / F means 31 activates the proficiency level predicting means 34.

  In the above description, it is assumed that the proficiency level prediction calculation unit 34 calculates the proficiency level using the number of correct answers and the number of incorrect answers. The degree may be calculated. On the other hand, the proficiency level may be predicted and calculated using parameters other than these, for example, the answer time for each question and the student's confidence in the question answer.

(Other examples of proficiency level prediction processing)
The proficiency level predicting process is not limited to a method in which the above-described student is currently performing, or a virtual setting that a problem to be performed in the future is correct, and may be performed by another method. For example, based on the answer history of students who have already passed the unit, the answer history of the calculation target student, the number of consecutive correct answers of the calculation target student, or the question that the calculation target student currently answers or plans to answer in the future By virtually setting the correctness / incorrectness, the proficiency level of the student can be predicted and calculated.

  Moreover, the predictor by a prior art can also be used. For example, as an example of a predictor, multiple regression analysis may be performed using correct / incorrect data for all problems as an explanatory variable and the number of problems required to pass a certain session as an objective variable. The explanatory variable and the target variable are not limited to this, and any variable may be selected as necessary, for example, time.

For example, as shown in FIG. 5, as shown in FIG. 5, for example, as shown in the first line, the student with the user ID 1 has passed unit 1 in 30 minutes and has not taken units 2 and 3. When hit, a table is generated that indicates that the required number of problems is 5 and the required time is 20 minutes when the unit Y1 is passed. Then, each parameter β0, β1,... Is obtained by the following multiple regression equation.
β0 + β1 ・ X1 + β2 ・ X2 + β3 ・ X3 + ・ ・ ・ = Y1
Then, for a student, Y1 is calculated from the learning history of the student using the values of X1, X2,... And each parameter (β0, β1,...), So that the student passes the unit Y1. Predict the number of problems or time to complete. Other units (Y2, Y3...) Can be similarly predicted using multiple regression equations.

(Action timing judgment process)
Next, the action timing determination means 35 will be described with reference to the flowchart shown in FIG.

  When the action timing determination unit 35 is activated in real time from the student terminal I / F unit 31 at a fixed period or when receiving data from the student terminal 3, the action timing determination unit 35 first accesses the learning status table 24 to determine whether or not it is in a learning session. Is determined (S201). As a result, if the learning session is not in progress (“NO” in S201), then the timer value and the new pass flag are extracted, the timer value is within a predetermined threshold (for example, 3 minutes), and the new pass flag is If it is set (“YES” in S202), the student is classified into the third group, and “3” is written in the display form column (not shown) of the student ID in the learning status table (S203). In other cases (“NO” in S202), the student is classified into the fourth group, and “4” is written in the display form column of the student ID in the learning status table (S204).

  On the other hand, if the learning session is in step S201 ("YES" in S201), it is next determined whether or not the session requires the effort (S205). For example, in the session, if the problem has never been wrongly solved or the lecture has never been taken, it can be determined that the student does not need any effort. If the determination result in step S205 is “NO”, the student is classified into the fourth group, and “4” is written in the display form column of the student ID in the learning status table (S206).

  If the result of determination in step S205 is “YES”, it is next determined whether or not the current learning session state is the end state by referring to the learning session flag in the learning state table (S207). If it is in a state (“YES” in S207), it is determined whether or not a new pass flag is set (S208). If it is set (“YES” in S208), the student is assigned to the first group. And “1” is written in the display form column of the student ID in the learning status table (S209). On the other hand, if the new pass flag is not set in step S208 (“NO” in S208), the student is classified into the fourth group, and “4” is written in the display form column of the student ID in the learning status table. (S204).

If the result of the determination in step S207 is that the current learning session state is not the end state (“NO” in S207), the proficiency level prediction value in the learning state table is extracted, and the minimum number of correct answers required to pass is “1”. It is determined whether or not this is the last problem in the session (S210). If the determination result in step S210 is “YES”, the student is classified into the second group, and “2” is written in the display form column of the student ID in the learning status table (S212).
On the other hand, if the determination result in step S210 is “NO”, the student is classified into the fourth group, and “4” is written in the display form column of the student ID in the learning status table (S206).

In the category (display form column) classified by the action timing determination means 35, the first group is the students who are at the call timing, the second group is the students who are about to have the call timing, the third group Is a little past the call timing, group 4 is the other students.
The learning status table 24 is updated by the above processing.

  Next, processing contents of the editing means 36 will be described. FIG. 7 is an example of a student list screen (coaching screen) displayed on the coach terminal 2. The items of the student name corresponding to the student ID, the session / unit being studied, the teaching material, the elapsed time, and the cochin glycomend are displayed. Here, the student group belonging to the first group is displayed at the top, the student group belonging to the second group is displayed next, and then the third group and the fourth group are sorted in order and displayed by color for each group. To do.

  The elapsed time is the elapsed time from the end of the session for the first group, the third group (the group at the end of the learning session), and the session start (or unit start) for the second group and the fourth group (the group during the learning session). In the time from, the content of the action that the coach should take such as calling is displayed in the Cochin Glycomend column.

  For example, for students belonging to Group 2 and Group 4, if the elapsed time from the start of the unit is more than a certain value, or if the number of failures is more than a certain value, the elapsed time or the number of times By displaying it in the Cochin Glycomend column, the coach can give advice to the student considering that information. For students belonging to the first group, the content of encouragement can be arranged in consideration of the elapsed time from the end of the session.

  As described above, according to the present embodiment, information effective for student guidance and learning follow-up, such as the timing of the call to the student, its type (whether encouragement or advice) or the content of the call, is notified to the coach at an appropriate timing. Can do. In this case, for example, when talking to students who have achieved their goals, such as passing, not only informing the coach that the students have achieved their goals when they have achieved their goals, but also using the proficiency level prediction means. The close student is discriminated accurately, and the student is identified and displayed on the coach terminal, so that the coach is given time to prepare in advance and can speak in a timely manner. In addition, by using the learning support system according to the present embodiment, it is not necessary to constantly monitor the progress of each student with a human system, so it is possible to speak to all students at a low cost without omission. .

[Second Embodiment]
Next, a second embodiment of the learning support system according to the present invention will be described.
The main difference from the first embodiment is that in each student category classified by the action timing determination means 35, there is provided a function for sorting from the highest priority information to be provided to the coach. . In order to realize this function, the processing procedure of the action timing determination means 35 is changed as described below. Since the other functions are the same as those in FIG. 1, the same symbols are assigned to the same symbols, and descriptions thereof are omitted.

Next, the operation of the learning support system 1 according to the present embodiment will be described focusing on the difference from the first embodiment.
After the proficiency level prediction calculation process, the action timing determination unit 35 executes the processing procedure shown in FIG. Hereinafter, the operation of the proficiency level prediction unit 34 according to the present embodiment will be described with reference to FIG.

  When the proficiency level predicting unit 34 is activated in real time such as sending a question or receiving an answer from the student terminal I / F unit 31 at regular intervals, the proficiency level predicting unit 34 accesses the learning status table 24 and executes the following processing for a student who requires action. (S302a, S302b). Whether or not action is required is determined by, for example, providing an action completed flag, setting an action completed flag for a student who has finished the action, and determining that a student who does not have the action completed flag set needs action You may do it.

  The action timing determination unit 35 first refers to the status of the learning status table 24 for each extracted student, and determines whether the learning session is in progress (S304). If it is during the learning session, it is determined whether or not there is a possibility of passing in the session (S304). In this process, for example, if a code that has no possibility of passing (for example, a numerical value “99”) is stored in the predicted value column until the student passes, there is no possibility of passing, and other numerical values within a predetermined range. If (numerical value appropriate as the number of questions to be correctly answered before passing) is stored, it can be determined that there is a possibility of passing.

  As a result of the determination in step S304, if it is determined that there is a possibility of passing, the student is classified into the second group (S306). If it is determined that there is no possibility of passing, the student is classified into the fourth group ( S305).

  On the other hand, if it is not in the learning session in step S303, it is next determined whether or not a new pass flag is set in the status of the learning status table 24 (S307). As a result, when the new pass flag is set, the student is classified into the first group (S308), and when the new pass flag is not set, the student is classified into the third group (S309). .

  Next, the action timing determination means 35 weights the values of the timer means 1 (38) and the timer means 2 (39) for the first group of students after performing the classification process of step 302a to step S302b for each student. And priorities are calculated (S311), and the students are sorted based on the priorities from the urgency and importance of actions (S301a, S310b).

As described in the first embodiment, the timer means 1 (38) and the timer means 2 (39) are provided for each student, and the timer means 1 (38) resets the time measurement every time the learning session ends. The timer means 2 (39) is a timer that restarts time measurement every time a learning session starts. When the value of the timer means 1 (38) is T1, the value of the timer means 2 (39) is T2, and the weighting coefficients are a and b (a, b> 0), the priority P is expressed by the following equation, for example: Can be obtained.
P = b · T2-a · T1
Then, the students are sorted from students with a high priority P.

The above calculation example highly evaluates students who took a lot of time to pass the study session, that is, those who had a hard time, and the time after the end of the study session, that is, a new pass is short. It is highly appreciated.
The evaluation parameter is not limited to the above, and for example, the number of times that the session is rejected may be added to the priority determination parameter.

  Next, the action timing determination unit 35 executes sort processing for the second group of students according to the following procedure (S312a, S312b). First, the time until the student passes the unit is predicted using the average answer time of the student (S313). The average answer time of a student may be the average answer time of the student's past questions, or the answers of other students who have completed the question for questions that the student is currently solving or will solve in the future. You may decide based on time. For example, timer means 3 (not shown) that restarts from the distribution of each question is provided, and sorting is performed by increasing the priority from the smallest value obtained by subtracting the value of timer means 3 from the average answer time (S314). . This priority determination method can accurately prioritize a student group who passes if the current distribution problem is correctly answered.

  The average answering time described above may be obtained from the average answering time of other students of the question, or a difference from the answering time of the question that the student has conducted since the start of the learning session, such as a deviation. You may make it calculate based on a value etc. As a result, when the answer time tends to be earlier than that of other students, the coach can be prepared in consideration of this, so the timing of speaking can be predicted more accurately. In addition, when the time to pass directly is obtained by multiple regression analysis, the calculation result may be used.

The action timing determination means 35 sorts the students of the first group and the second group that have been prioritized by the above-described processing via the editing means 36 based on the priority order, and displays and outputs them on the coach terminal 2. . At this time, if necessary, students classified into other groups may be identified and displayed.
The action target student is identified and displayed on the coach terminal 2 by the above procedure.

In addition, although the example which performs a sort process about the student which belongs to the 1st group and the 2nd group was shown in FIG. 8, it is not limited to this, for example, about the student who has no possibility of the 4th group passing, The coaches may sort in the order of the number of occurrences or the longest time during the learning session, and the coach may speak according to the display order.
Note that the editing unit 36 may identify and display only the students with the highest priority instead of displaying them in the sort order.

  As described above, according to the present embodiment, in addition to the effects of the first embodiment, it is possible to take action correspondence in order from the student with the highest priority among the students that need action correspondence. In addition, it is possible to accurately recognize students who need an action soon.

The present invention is not limited to the above-described embodiment, and can be variously modified and realized without departing from the scope of the invention.
For example, in the above description, whether or not an action is required is determined based on whether or not the session has passed by comparing with a preset pass threshold. The determination may be made based on whether or not the target value is exceeded. In addition, a table in which the target value is associated with the action content may be provided, which target value is achieved may be identified and displayed on the coach terminal, and the coach may take an action according to the target value.

  Also, a table associating students with seat positions as shown in FIG. 9 is provided, and as shown in FIG. 10, the seat positions of students to be acted on, that is, students classified into the first group, are displayed on the coach terminal screen. You may do it.

  In the above description, the learning status list data generated by the learning support device 10 is displayed on the coach terminal 2 via the communication network. However, the stand-alone learning support device 10 is provided with a display device, and the display device A learning status list may be displayed on the screen. Of course, instead of the display device, or other output means such as an audio output device may be provided together with the display device, the learning status list information may be output for each category by a method other than the display of sound or the like.

DESCRIPTION OF SYMBOLS 1 Learning support system 2 Coach terminal 3 Student terminal 4 Communication network 10 Learning support apparatus 11 Transmission / reception part 12 Storage part 13 Arithmetic processing part 21 Student DB
22 Educational content DB
23 Course History DB
24 learning status table 31 student terminal I / F means 32 proficiency level calculation means 33 new pass determination means 33 proficiency level prediction means 34 proficiency level prediction means 35 action timing determination means 36 editing means 37 coach terminal I / F means 38 timer means 1
39 Timer means 2

Claims (5)

This is a learning support device that stores questions to be asked for each unit, provides students with questions that belong to the unit that the student takes, and inputs the answer data to calculate the timing of the action to be taken by the coach who teaches the student. And
For each learning session that defines the type of action, questions that belong to one or more units are extracted, the extracted questions are provided to the student, answer data is input, and whether the student has finished the learning session Means for inputting learning status data including
A proficiency level calculating means for calculating the proficiency level of the student for the unit to which the problem provided to the student belongs based on the input answer data, and determining whether the proficiency level has reached a threshold;
A proficiency level prediction means for calculating the future proficiency level of the student for the unit that the student takes,
Classifying each student into one of a plurality of categories using at least one of the learning status data of each student, the calculation result of the proficiency level calculation means, and the calculation result of the proficiency level prediction means Action timing determination means for
An editing means for generating a list of learning statuses of the student by making it possible to identify which of the categories the student belongs to;
An output means for outputting the learning status list data;
A learning support apparatus characterized by comprising:   The proficiency level predicting means calculates the number of questions that should be correctly answered before the proficiency level becomes equal to or higher than a threshold value as a future proficiency level or the time until the proficiency level exceeds a threshold value. The learning support apparatus described. Each student has a timer means that starts from the end of the learning session,
The action timing determination means calculates a priority order using a value of the timer means for a student who needs an action,
The learning support apparatus according to claim 1, wherein the editing unit generates the learning status list data based on the priority order. The learning support apparatus according to any one of claims 1 to 3,
Connect to the terminal device on the student side and the terminal device on the coach side via the communication network,
The learning support device, wherein the answer data and the learning status data are input through the student side terminal device, and the learning status list data is output to the coach side terminal device. This is a computer program that stores questions to be asked for each unit, provides students with questions that belong to the unit that the student takes, and inputs the answer data to calculate the timing of the actions to be taken by the coach who teaches the student. And
The computer extracts questions belonging to one or more units for each learning session that determines the type of action, provides the extracted questions to the student, inputs answer data, and the student ends the learning session. Means for inputting learning status data including whether or not
A proficiency level calculating means for calculating the proficiency level of the student with respect to the unit to which the problem provided to the student belongs based on the input answer data, and determining whether the proficiency level has reached a threshold;
A proficiency level predictor that calculates the student's future proficiency level for the unit that the student takes,
Classifying each student into one of a plurality of categories using at least one of the learning status data of each student, the calculation result of the proficiency level calculation means, and the calculation result of the proficiency level prediction means Action timing determination means for
Editing means for generating a list of learning statuses of students by identifying which of the categories the student belongs to;
An output means for outputting the learning status list data;
Program to function as.